LO 3.2: Explain the significant difficulties in backtesting a VaR model.

LO 3.2: Explain the significant difficulties in backtesting a VaR model.
VaR models are based on static portfolios, while actual portfolio compositions are constantly changing as relative prices change and positions are bought and sold. Multiple risk factors affect actual profit and loss, but they are not included in the VaR model. For example, the actual returns are complicated by intraday changes as well as profit and loss factors that result from commissions, fees, interest income, and bid-ask spreads. Such effects can be minimized by backtesting with a relatively short time horizon such as a daily holding period.
Another difficulty with backtesting is that the sample backtested may not be representative of the true underlying risk. The backtesting period constitutes a limited sample, so we do not expect to find the predicted number of exceptions in every sample. At some level, we must reject the model, which suggests the need to find an acceptable level of exceptions.
Risk managers should track both actual and hypothetical returns that reflect VaR expectations. The VaR modeled returns are comparable to the hypothetical return that would be experienced had the portfolio remained constant for the holding period. Generally, we compare the VaR model returns to cleaned returns (i.e., actual returns adjusted for all changes that arise from changes that are not marked to market, like funding costs and fee income). Both actual and hypothetical returns should be backtested to verify the validity of the VaR model, and the VaR modeling methodology should be adjusted if hypothetical returns fail when backtesting.
U sing Failure Rates in M odel Verification

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